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dc.contributor.authorConsoli, S-
dc.contributor.authorMoreno-Pérez, J A-
dc.contributor.authorDarby-Dowman, K-
dc.contributor.authorMladenović, N-
dc.description.abstractParticle Swarm Optimization is an evolutionary method inspired by the social behaviour of individuals inside swarms in nature. Solutions of the problem are modelled as members of the swarm which fly in the solution space. The evolution is obtained from the continuous movement of the particles that constitute the swarm submitted to the effect of the inertia and the attraction of the members who lead the swarm. This work focuses on a recent Discrete Particle Swarm Optimization for combinatorial optimization, called Jumping Particle Swarm Optimization. Its effectiveness is illustrated on the minimum labelling Steiner tree problem: given an undirected labelled connected graph, the aim is to find a spanning tree covering a given subset of nodes, whose edges have the smallest number of distinct labels.en
dc.format.extent226150 bytes-
dc.subjectCombinatorial optimizationen
dc.subjectDiscrete Particle Swarm Optimizationen
dc.subjectMinimum labelling Steiner tree problemen
dc.subjectGraphs and Networksen
dc.titleDiscrete Particle Swarm Optimization for the minimum labelling Steiner tree problemen
dc.typeWorking Paperen
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Dept of Mathematics Research Papers
Mathematical Sciences

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